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1. 使用matlab自带的人脸识别工具(Viola-Jones算法)找出人脸的位置,并裁剪出人脸区域。
2. 使用Gabor滤波器识别出人脸的局部特征及纹理。
3. 训练一个SVM进行表情分类。
4. 交叉验证得到表情分类正确率为83.3 。
操作说明和系统描述请见ReadMe.-1. Using matlab with face detection tool (Viola-Jones algorithm) to find the location of a human
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利用matlab实现NLDA人脸识别算法,更详细的random sampling LDA, bagging NLDA和整合LDA算子利用majority vote 和sum rule的matlab 代码,人脸库使用ORL库或者XM2VTS库,地址:http://shop.zbj.com/14563255/sid-1213623.html- matlab codes for NLDA face detection, the face s are ORL. More details about r
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利用matlab工具,实现了对图像中的人脸区域进行检测,并标记出来,也能够在具有多个人脸的图像中实现。-Using matlab tool to achieve the image of the face area of the detection, and marked out, but also in a number of faces with the image to achieve.
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利用积分图的方式提取图像hog特征,用于人脸、行人检测。(Using the integral plot to extract the image hog feature, for human face, pedestrian detection.)
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采用MATLAB完成人脸检测,可实现在前景和背景差别较大的情况下完成检测,准确率较高,适用范围较广。(Using MATLAB to complete the face detection can realize the detection of the foreground and the background difference is bigger, the accuracy rate is high, and the scope of application is wider.)
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对人脸识别的基本进程进行综述,介绍了空间转换及识别的方法;采用低通滤波处理策略,在总结和分析这些处理方法的基础上,运用填孔处理和边缘检测的人脸识别方法进行人脸识别工作;将几种边缘检测算法与人脸识别相结合进行检测,其识别率有可观的提升。(The basic process of face recognition is reviewed, and the method of space conversion and recognition is introduced. On the basis of
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